(1) Field of the Invention
The present invention relates to remote sensing and remote imaging, and more specifically to a method for processing hyper-spectral remote sensor data for the purpose of displaying the spatial tracks of energy sources in multi-spectral images corresponding to the sensor data.
(2) Description of the Prior Art
Remote sensing of the energy signals of a moving vehicle or energy source for the purposes of tracking the vehicle or energy source has often been accomplished by measuring the intensity of the energy signals with sensors specifically designed to detect energy intensity. In remote sensing applications the sensor is often a planar array of sensing cells, each cell responding to the energy incident on its corresponding section of the array surface. In other applications, such as acoustic sensing, the received energy on sensor elements must be interpreted through a beam forming function to yield energy intensity in a set of spatially directed cells (more commonly called beams). Such a method is designed to track energy peaks as they move over time on the given set of sensor cells. The total broadband energy is plotted and visually displayed. Targets appear as peaks of energy in the display, and are tracked. One method of target tracking based on sensor level data is the Histogram Probabilistic Multi-Hypothesis Tracking (H-PMHT) algorithm. It is an application of the Expectation-Maximization (EM) method of target tracking. It uses a synthetic (multi-dimensional) histogram interpretation of the received power levels in all of the sensor cells. The data for the H-PMHT algorithm usually consists of broadband intensities on a set of spatial sensor cells. The H-PMHT algorithm has its limitations. For example, in situations where more than one target is being tracked and the targets cross paths, the intensity of the energy signals of the targets merge, making it impossible to distinguish the energy between the two targets. In such a situation, the targets must be reacquired by the sensors after they have crossed resulting in a gap and delay in tracking information.
U.S. patent application Ser. No. 10/214,551 to Struzinski teaches a method and system for predicting and detecting the crossing of two target tracks in a bearing versus time coordinate frame. The method/system uses a series of periodic bearing measurements of the two target tracks to determine a bearing rate and a projected intercept with a bearing axis of the bearing versus time coordinate frame. A crossing time tc for the two target tracks is determined using the tracks' bearing rates and projected intercepts. A prediction that the two target tracks will cross results if a first inequality is satisfied while a detection that the two target tracks have crossed results if a second inequality is satisfied. This method does not, however, address the problem of distinguishing between and identifying the targets before, during and after they have crossed.
There is currently no reliable method by which targets can be consistently tracked and distinguished as they cross paths. What is needed is a method for tracking targets that does not rely solely on broadband energy signal intensity, but also utilizes the spectral aspects of the energy signal, combining both intensity and spectral data so that crossing targets can be tracked provided they have some degree of spectral distinction.